This book bridges the latest software applications with the
benefits of modern resampling techniques

Resampling helps students understand the meaning of sampling
distributions, sampling variability, P-values, hypothesis tests,
and confidence intervals. This groundbreaking book shows how to
apply modern resampling techniques to mathematical statistics.
Extensively class-tested to ensure an accessible presentation,
Mathematical Statistics with Resampling and R utilizes the
powerful and flexible computer language R to underscore the
significance and benefits of modern resampling techniques.

The book begins by introducing permutation tests and bootstrap
methods, motivating classical inference methods. Striking a balance
between theory, computing, and applications, the authors explore
additional topics such as:

Exploratory data analysis

Calculation of sampling distributions

The Central Limit Theorem

Monte Carlo sampling

Maximum likelihood estimation and properties of estimators

Confidence intervals and hypothesis tests

Regression

Bayesian methods

Throughout the book, case studies on diverse subjects such as
flight delays, birth weights of babies, and telephone company
repair times illustrate the relevance of the real-world
applications of the discussed material. Key definitions and
theorems of important probability distributions are collected at
the end of the book, and a related website is also available,
featuring additional material including data sets, R scripts, and
helpful teaching hints.

Mathematical Statistics with Resampling and R
is an excellent book for courses on mathematical statistics at the
upper-undergraduate and graduate levels. It also serves as a
valuable reference for applied statisticians working in the areas
of business, economics, biostatistics, and public health who
utilize resampling methods in their everyday work.

LAURA CHIHARA, PhD, is Professor of Mathematics at Carleton
College. She has extensive experience teaching mathematical
statistics and applied regression analysis. She has supervised
undergraduates working on statistics projects for local businesses
and organizations such as Target Corporation and the Minnesota
Pollution Control Agency. Dr. Chihara has experience with S+ and R
from her work at Insightful Corporation (formerly MathSoft) and in
statistical consulting.

TIM HESTERBERG, PhD, is Senior Ads Quality Statistician
at Google. He was a senior research scientist for Insightful
Corporation and led the development of S+Resample and other S+ and
R software. Dr. Hesterberg has published numerous articles in the
areas of bootstrap and related resampling techniques, Monte Carlo
simulation methodology, modern regression, tectonic deformation
estimation, and electric demand forecasting.

"Mathematical Statistics with Resampling and R is a great resource for intermediate and advanced statistics students who want to achieve an indepth understanding of resampling techniques backed by practical implementation." (Book Pleasures, 2012)

"It is highly recommended to someone with a good background in mathematics, probability, and basic statistics who wants to learn about the theory and about resampling and how it relates to traditional methods, and how to implement resamplinjg in R. The book is also a wonderful source of simulations to support the teaching of statistics." (Journal of Biopharmaceutical Statistics, 2011)

"It is less demanding mathematically, more applied in its emphasis, and more modern in content than the usual book, which makes it a good choice if you want a modern applied book at the level of Larsen and Marx (1986)."- George W. Cobb, Mount Holyoke College Department of Mathematics and Statsitics (Chilean Journal of Statistics, 1 April 2011)

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